Technology is the application of knowledge to practical
pursuits. Information relevant to technology is the subject of various
types of documents, including: scholarly publications (journals,
conference proceedings, abstracts, grant applications, textbooks);
legal documents (patents, contracts, legislation); and more public
venues (magazines, webpages, blogs, financial reports). Interest in
the automatic classification of technical documents has recently been
growing and Natural Language Processing is a major component of such
classification systems. On a "synchronic" level, there has been
considerable efforts towards: genre classification, citation
sentiment, relation extraction, terminology extraction, and other
areas. On the "diachronic" level, the field of technology forecasting
is on the rise because both government agencies and businesses are
looking to automatically detect and classify trends in technology, in
order to help guide them with resource and financial investments.

This workshop aims to bring together natural language processing
research applying to technical documents. The goal is to explore
techniques which apply across multiple domains and genres (and are not
biased towards biomedical, computer science, or other specific
genres). The results should either be: a) synchronic in nature,
relating to the processing or analysis of text, documents or sets of
documents without consideration of time; or b) diachronic in nature,
investigating how linguistic features change over time, e.g., by the
comparison of documents from different time periods.

Subject areas include topics specific to the study of technical
documents such as:

Another major focus of this workshop is to explore how synchronic and
diachronic topics relate to each other. For example, we encourage
synchronic papers to discuss how and why such features may vary over
time, e.g., trends in sentiment attributed to citations may indicate
changes in the status of a paper. Diachronic papers are encouraged to
discuss any synchronic features used that have been tracked over time.

Modes of Presentations: Submissions may be for oral or poster
presentations. We assume that there is no difference in quality
between oral and poster presentations, but that some ideas are more
appropriately conveyed in one mode or the other.

Olga Babko-Malaya, BAE Systems
Josef van Genabith, Dublin City University
Ralph Grishman, New York University (Co-Chair)
Yifan He, New York University (Co-Chair)
Kris Jack, Mendeley
Min-Yen Kan, National University of Singapore
Roman Kern, Know-Center
Adam Meyers, New York University (Co-Chair)
Arzucan Özgür, Bogazici University
James Pustejovsky, Brandeis University
Dragomir Radev, University of Michigan
Ulrich Schäfer, DFKI
Simone Teufel, University of Cambridge
Marc Verhagen, Brandeis University
Nianwen Xue, Brandeis University